Python Developer ? GenAI & Agentic AI

Job Description

?? Hiring: Python Developer ? GenAI & Agentic AI | 5?7 Years | Bangalore/Remote | Immediate Joiners ?? Location: Bangalore / Remote ?? Experience: 5?7 Years ?? Budget: 1.6 ? 1.7 LPM ?? Notice Period: Immediate (Bench resources only) ?? Mode: Remote/Hybrid ?? Note: Candidates must have ESI/Medical Insurance, EPFO Registration, PT Registration, Labour Welfare Fund Registration, Shop Act Registration, and GST Registration . Only profiles with these compliance documents will be considered. ? About the Role We are looking for an experienced Python Developer specialized in Generative AI (GenAI) and Agentic AI . The ideal candidate will be proficient in LLM-based application development, RAG pipelines, AI agents, LangChain/LangGraph, and cloud AI services. You will design and deploy scalable AI-driven solutions used across enterprise environments. ?? Key Responsibilities Develop GenAI Applications: Build and optimize AI solutions using Python, LangChain, LangGraph, MCP, and AgentOps. LLM Integration: Work with Azure AI, AWS Bedrock, OpenAI, Anthropic, and other LLM providers for text, multimodal, and agent workflows. RAG Architecture: Implement Retrieval-Augmented Generation pipelines with vector DBs (Pinecone, Chroma, Weaviate, FAISS). Fine-tuning & MLOps: Fine-tune LLMs for domain tasks; build CI/CD pipelines for ML models using MLOps tools and best practices. Agentic AI Systems: Design multi-agent workflows with orchestration, memory, planning, and error-handling capabilities. Cloud Deployment: Deploy models/applications on AWS (Lambda, EC2, S3, Bedrock, SageMaker) and Azure AI. Performance & Cost Optimization: Optimize model response time, scalability, and cloud compute cost. Cross-functional Collaboration: Work closely with Data Science, DevOps, and Product teams to deliver robust AI solutions. ?? Required Skills & Qualifications Strong proficiency in Python and backend development. Hands-on experience with LangChain, LangGraph, MCP, AgentOps . Strong understanding of RAG pipelines and vector DBs (Pinecone, Chroma, Weaviate, FAISS). Experience in LLM fine-tuning and prompt engineering. Solid knowledge of MLOps (CI/CD, monitoring, model deployment). Experience using cloud AI platforms: AWS Bedrock, Azure AI, SageMaker, GCP Vertex AI (preferred). Understanding of Agentic AI (multi-agent orchestration, planning, memory). Familiarity with Docker, Kubernetes, Terraform, GitOps . Strong analytical, debugging, and problem-solving skills. ? Preferred Qualifications Experience with multimodal models (text, image, audio). Exposure to enterprise AI compliance and security frameworks . Knowledge of ISO/IEC AI governance standards . Contributions to open-source AI/ML projects . ?? How to Apply If your profile matches and you meet the compliance requirements, please share your resume at [Add Email / Apply Link] . Immediate joiners are highly preferred.